NBLAST Flycircuit PNs (glom=="VAsomething") against FAFB PNs of VAs glomeruli

170201-nblast_against_FAFB_for_flycircuit_VAsomething.R

# Use NBLAST against PNs of identified VA__ glomeruli in FAFB to see what VA is Flycircuit PNs with glom=="VAsomething"?

# general packages
library(magrittr)
library(dplyr)
library(doMC)
registerDoMC(4)

# neuro packages
library(catmaid)
library(flycircuit)
library(elmr)
library(nat.nblast)
library(nat)

# Load your FAFB credential. I name it fafb_conn here.

# download FAFB PNs annotated with "^glomerulus VA"
# turn out, there are 9: "VA1d", "VA1v", "VA2",	"VA3",	"VA4", "VA5", "VA6", "VA7l", "VA7m".
# transform to common template with flycircuit (FCWB)
fafb_vas=read.neurons.catmaid("annotation:^glomerulus VA", conn=fafb_conn) %>%
  xform_brain(sample=FAFB13, reference=FCWB)

# load flycircuit 2 glom==VAsomething PNs
fc_vas=flycircuit::load_si_data('allpndps.rds') %>%
  subset(glom=="VAsomething") %>% 
  mirror_brain(brain=FCWB, tranform='flip')

# a function to do nblast and order results according to mean scores
# also show identified glom from FAFB in the neuron name
nblast_against_fafb <- function(query, targets, conn) {
  sc=nblast(query, targets, normalised=TRUE)
  scr=nblast(targets, query, normalised=TRUE)
  data.frame(score=sc, score_r=scr, muscore=(sc+scr)/2) %>%
    .[order(.$muscore, decreasing = T), ] %>%
    mutate(skids=as.numeric(row.names(.)), fafb_gloms=catmaid_get_neuronnames(skids, conn=conn))
}

# run it for two VAsomething PNs in Flycircuit
VA_1st = nblast_against_fafb(fc_vas[[1]], dotprops(fafb_vas)) %T>% print
VA_2nd = nblast_against_fafb(fc_vas[[2]], dotprops(fafb_vas)) %T>% print

# top hit for both VAsomething PNs are all VA4 in FAFB!

# plot them, they look like VA4 as well.